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What is a high density region?
A highest posterior density [interval] is basically the shortest interval on a posterior density for some given confidence level. A highest density region is probably the same idea applied to any arbitrary density, so not necessarily a posterior distribution.
How do you convert density to bulk density?
For example, to convert from lb/ft3 to g/mL you would multiply by 16.018463 then divide by 1000. Or, multiply by 16.018463/1000 = 0.016018463. So, to convert directly from lb/ft3 to g/mL you multiply by 0.016018463.
Which is the highest posterior density interval in hdinterval?
This is often applied to a Bayesian posterior distribution and is then termed “highest posterior density interval”, but can be applied to any distribution, including priors. The function is an S3 generic, with methods for a range of input objects. hdi (object, credMass = 0.95.)
What is the 95% density interval ( HDI )?
87. The 95% HDI consists of those values of θ that have at least some minimal level of posterior credibility, such that the total probability of all such θ values is 95%. Let’s consider the HDI when we flip a coin and observe z = 7 and N = 24.
Which is the highest density interval in Bayesian data analysis?
John K. Kruschke, in Doing Bayesian Data Analysis (Second Edition), 2015 Another way of summarizing a distribution, which we will use often, is the highest density interval, abbreviated HDI.6 The HDI indicates which points of a distribution are most credible, and which cover most of the distribution.
How to calculate the highest density interval in rjags?
For the rjags package, rjags::coda.samples produces a mcmc.list object and rjags::jags.samples produces a list of mcarray objects. None of the above use interpolation: the values returned correspond to specific values in the data object, and will be conservative (ie, too wide rather than too narrow).